Geological formation and log visualization

ABSTRACT

In some examples, a system may receive log data including a depth-series of data for a sensed parameter. The system may determine a parameter value of the depth series data for individual subunits of depth corresponding to a larger unit of depth. The system may further determine a scale of graphic effects corresponding to parameter values for the depth-series data. The system may present, on a display, a visualization of the depth-series data. For instance, the visualization may include a plurality of cells arranged in a plurality of rows, with each cell corresponding to the larger unit of depth and including a plurality of subcells corresponding to the subunits of depth. Additionally, each subcell may be presented with a respective graphic effect corresponding to the parameter value determined at a corresponding depth, and the graphic effect may correspond to the parameter value on the scale of graphic effects.

BACKGROUND

Well boreholes may be drilled into the earth for locating and accessingfossil fuel deposits, groundwater, and the like, as well as for mineralexploration, geothermal exploration, environmental and geotechnicalstudies, and so forth. To aid in identifying geological formations, welllogs may be generated to provide detailed information of the geologicalformations penetrated by a borehole, such as for determining the contentof the earth adjacent to the borehole. For instance, in petroleumexploration and development, geological formation evaluation based onwell logs may be used to determine the ability of a borehole to producepetroleum, and may be further used for determining casing decisions, andthe like, which may subsequently affect the stability of an oil well. Insome cases, the well log may be generated based on physical measurementsmade by instruments lowered into the borehole. Conventionally, well logsmay be printed out as paper charts, often many feet long, which may bedifficult to evaluate. For example, as the depth of boreholes continuesto increase, the paper charts are becoming longer, which can lead toloss of spatial context when analyzing the paper charts. Furthermore,comparing such charts of multiple wells concurrently can be cumbersome.

SUMMARY

Some implementations include arrangements and techniques for presentinga visualization of log data. For example, a system may receive log dataincluding a depth-series of data for a sensed parameter. The system maydetermine a parameter value of the depth series data for individualsubunits of depth corresponding to a larger unit of depth. The systemmay further determine a scale of graphic effects corresponding toparameter values for the depth-series data. The system may present, on adisplay, a visualization of the depth-series data. For instance, thevisualization may include a plurality of cells arranged in a pluralityof rows, with each cell corresponding to the larger unit of depth andincluding a plurality of subcells corresponding to the subunits ofdepth. Additionally, each subcell may be presented with a respectivegraphic effect corresponding to the parameter value determined at acorresponding depth, and the graphic effect may correspond to theparameter value on the scale of graphic effects. Additionally, in someexamples, an indicator may be included between a first plurality of therows and a second plurality of the rows to indicate a change ingeological formation.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is set forth with reference to the accompanyingfigures. In the figures, the left-most digit(s) of a reference numberidentifies the figure in which the reference number first appears. Theuse of the same reference numbers in different figures indicates similaror identical items or features.

FIG. 1 illustrates an example architecture of a system able to present alog data visualization according to some implementations.

FIG. 2 illustrates an example GUI that may be generated for visualizingdata according to some implementations.

FIG. 3 illustrates an enlarged view of a log data visualizationincluding details of individual subcells within individual cellsaccording to some implementations.

FIG. 4 illustrates an example LAS data structure of an LAS file for awell log according to some implementations.

FIG. 5 illustrates an example of the formation information datastructure according to some implementations.

FIG. 6 is a flow diagram illustrating an example process for generatinga GUI according to some implementations.

FIG. 7 illustrates an example of determining subcell values for subcellsof a cell according to some implementations.

FIG. 8 illustrates an enlarged view of applying additional graphiceffects to the subcells to convey additional information according tosome implementations.

FIG. 9 illustrates an example GUI for comparing a parameter for twodifferent wells concurrently according to some implementations.

DETAILED DESCRIPTION

Some implementations herein are directed to techniques and arrangementsfor efficient and compact cell-based visualization of well loginformation. The cell-based visualization for well logs described hereinis space efficient, retains context, and enables comparison of theresults from multiple wells side-by-side concurrently on a singledisplay. For instance, rather than linearly increasing the depth alongthe y-axis to visualize the well log parameters, as in conventionalvisualization techniques, implementations herein generate and present apattern of blocks of cells and subcells in a graphic user interface(GUI).

In some examples, the multiple cells may be grouped or otherwisearranged into multiple blocks of multiple cells. Each block maycorrespond to an individual geological formation, and the blocks andcells in each block may be ordered in a sequence according to the orderin which the formations occur in the earth. Further, each cell mayinclude a plurality of regularly arranged subcells. For instance, eachcell and each subcell within each cell may correspond to the parameterinformation determined for a specified depth. Furthermore, each subcell,and thus, each cell, may include a graphic effect, such as a selectedcolor, a selected pattern, a selected brightness, or the like, thatcorresponds to a value of the parameter at the specified depth. Thus,the GUI herein provides a compact intuitive view of a well log thatconveys meaningful information representative of one or more measuredparameters. Further, the GUI may provide a clear indication of thenumber and location of the different geological formations relative toeach other, with demarcations between the respective geologicalformations.

In some examples, the cell-based visualization herein may be generatedbased on measured parameters determined from processing raw well logdata. The raw data may initially be stored as a Log ASCII Standard (LAS)file or other suitable file type and processed to determine values forthe cells and subcells. Additionally, the cell-based visualization mayfurther be generated based on geological formation data that isavailable, e.g., from a separate table, database, or other geologicalformation data structure. For example, formation top depths and labelsmay be determined from the geological formation data structure.

In some cases, the well log may include a parameter that is measured asan amplitude that varies based on the content of the earth detectedadjacent to the borehole. The system herein may determine the averageamplitude or other average value of the parameter over a specified unitof depth, such as a foot, half foot, tenth of a meter, half meter, etc.The specified unit of depth may correspond to an individual subcell inone of the cells, and each cell may correspond to a larger specifiedunit of depth, such as 5 feet, 10 feet, 2 meters, 3 meters, etc. Forexample, each cell may include a plurality of subcells, such as 4, 6, 8,10, etc. In some cases, the average values of the parameter for eachsubcell may be determined in advance and stored in a subcell value datastructure for the well log to enable the GUI to be generated quickly byaccessing the data structure, rather than computing average parametervalues each time the GUI is generated.

When the GUI is generated, a graphic effect may be applied to eachsubcell in each cell in each block to represent the average parametervalue for each individual subcell. Examples of graphic effects includedifferent colors for different ranges of parameter values; differentpatterns, such as cross hatching, stippling, or the like, for differentranges of parameter values; and/or different levels of brightness fordifferent ranges of parameter values. Further, while several examples ofgraphic effects are described herein, implementations are not limited toany particular type of graphic effect.

Furthermore, in some examples, additional graphic effects may be appliedto individual subcells to indicate a trend of the parameter measurement.For example, if the value of the parameter is increasing more than athreshold amount, the subcell may have a first graphic effect applied.If the value of the parameter is decreasing more than a thresholdamount, the subcell may have a second graphic effect applied. If thevalue is neither decreasing nor increasing more than the respectivethresholds, no graphic effect might be applied in some cases, or inother cases a third graphic effect may be applied.

For discussion purposes, some example implementations are described inthe environment of a computing device that presents a GUI providing avisualization of well log information or the like. However,implementations herein are not limited to the specific examplesprovided, and may be extended to other types of data, other types ofenvironments, other system architectures, other graphics effects, and soforth, as will be apparent to those of skill in the art in light of thedisclosure herein. For instance, the implementations herein may includecollecting sensor data (e.g., Gamma Ray (GR) data and/or otherparameters) about lithology using various systems such as Logging WhileDrilling (LWD), Measurement While Drilling (MWD), and so forth. Someexamples may be used by oil and gas operators, service providers,researchers, and the like, for visualization of drilling parameter logs,other types of well logs, other types of data, and so forth.

FIG. 1 illustrates an example architecture of a system 100 able topresent a log data visualization according to some implementations. Thesystem 100 includes at least one visualization computing device 102 thatis able to communicate with at least one well logging computing device104, such as through one or more networks 106. In addition, thevisualization computing device(s) 102 may communicate over the one ormore networks 106 with one or more information server computing devices108.

In some examples, the visualization computing device(s) 102, welllogging computing device(s) 104, and/or information server computingdevice(s) 108 may include one or more servers, personal computers, orother types of computing devices that may be embodied in any number ofways. For example, in the case of a personal computer, the programs,other functional components, and at least a portion of data storage maybe implemented on the personal computer and/or may be partiallyimplemented at a network location, such as through cloud-based storage,cloud-based processing, or the like. Alternatively, in the case of aserver, the programs, other functional components, and at least aportion of data storage may be implemented on at least one server, suchas a stand-alone server, or a server in a cluster of servers, a serverfarm or data center, a cloud-hosted computing service, and so forth,although other computer architectures may additionally or alternativelybe used.

In the illustrated example, the visualization computing device 102includes, or may have associated therewith, one or more processors 112,one or more communication interfaces (I/Fs) 114, and one or morecomputer-readable media 116. Each processor 112 may be a singleprocessing unit or a number of processing units, and may include singleor multiple computing units, or multiple processing cores. Theprocessor(s) 112 can be implemented as one or more central processingunits, microprocessors, microcomputers, microcontrollers, digital signalprocessors, state machines, logic circuitries, graphics processingunits, systems on chips, and/or any devices that manipulate signalsbased on operational instructions. For instance, the processor(s) 112may be one or more hardware processors and/or logic circuits of anysuitable type specifically programmed or configured to execute thealgorithms and processes described herein. The processor(s) 112 may beconfigured to fetch and execute computer-readable instructions stored inthe computer-readable media 116, which can program the processor(s) 112to perform the functions described herein.

The computer-readable media 116 may include volatile and nonvolatilememory and/or removable and non-removable media implemented in any typeof technology for storage of information such as computer-readableinstructions, data structures, program modules, or other data. Forexample, the computer-readable media 116 may include, but is not limitedto, RAM, ROM, EEPROM, flash memory or other memory technology, opticalstorage, solid state storage, magnetic tape, magnetic disk storage, RAIDstorage systems, storage arrays, network attached storage, storage areanetworks, cloud storage, or any other medium that can be used to storethe desired information and that can be accessed by a computing device.Depending on the configuration of the visualization computing device102, the computer-readable media 116 may be a tangible non-transitorymedium to the extent that, when mentioned, non-transitorycomputer-readable media exclude media such as energy, carrier signals,electromagnetic waves, and/or signals per se. In some cases, thecomputer-readable media 116 may be at the same location as thevisualization computing device 102, while in other examples, thecomputer-readable media 116 may be partially remote from thevisualization computing device 102.

The computer-readable media 116 may be used to store any number offunctional components that are executable by the processor(s) 112. Inmany implementations, these functional components comprise instructionsor programs that are executable by the processor(s) 112 and that, whenexecuted, specifically program the processor(s) 112 to perform theactions attributed herein to the visualization computing device 102.Functional components stored in the computer-readable media 116 mayinclude a data visualization program 118. The data visualization program118 may include one or more computer programs, computer-readableinstructions, executable code, or portions thereof that are executableto cause the processor(s) 112 to receive one or more well logs 120 andprocess the well logs 120 according to the rules defined herein forgenerating one or more subcell parameter value data structures 122. Thedata visualization program 118 may further generate a graphic userinterface (GUI) (not shown in FIG. 1) from the well log(s) 120, thesubcell parameter value data structure 122, and a formation informationdata structure 124, as described additionally below.

Additional functional components maintained in the computer-readablemedia 116 of the visualization computing device(s) 102 may include anoperating system (not shown in FIG. 1) that may control and managevarious functions of the visualization computing device 102. In somecases, the functional components may be stored in a storage portion ofthe computer-readable media 116, loaded into a local memory portion ofthe computer-readable media 116, and executed by the one or moreprocessors 112. Numerous other software and/or hardware configurationswill be apparent to those of skill in the art having the benefit of thedisclosure herein.

In addition, the computer-readable media 116 may store data and datastructures used for performing the functions and services describedherein. For example, the computer-readable media 116 may store the welllogs 120, each of which may include well log metadata 126 and well logdata 128. The computer-readable media 116 may further store the subcellparameter value data structure(s) 122 and the formation information datastructure 124, as mentioned above.

The visualization computing device 102 may also include or maintainother functional components and data, which may include programs,drivers, etc., and other data used or generated by the functionalcomponents. Further, the visualization computing device 102 may includemany other logical, programmatic, and physical components, of whichthose described above are merely examples that are related to thediscussion herein.

The visualization computing device 102 may further include or mayotherwise be in communication with a display 130 for presenting the GUIincluding the well log visualization to a user 132. As mentionedpreviously, the well logs herein may be used by oil and gas operators,service providers, researchers, and the like, such as for visualizationof drilling parameter logs, other types of well logs, and other types ofdata. For instance, in other cases, the techniques herein may be used topresent time-series data rather that depth-series data. The user 132 mayexecute and interact with the data visualization program 118 to causepresentation of the GUI on the display 130.

Additionally, in some examples, a first portion of the operationsdescribed herein may be performed by a first one of the visualizationcomputing devices 102, and another portion of the operations may beperformed by a second one of the visualization computing devices 102. Asone example, one or more first visualization computing devices 102 mayexecute the data visualization program 118 to access the well logs 120and generate the subcell parameter value data structure 122, while oneor more second visualization computing devices 102 may execute the datavisualization program 118 to generate the GUI using one or morecorresponding subcell parameter value data structures 122. As oneexample, the user 132 may use a browser or the like on the secondvisualization computing device 102 to access the first visualizationcomputing device 102 to cause the GUI to be presented on the display130, which may be associated with the second visualization computingdevice 102. Alternatively, as still another example, the visualizationcomputing device 102 and the well logging computing device 104 may bethe same computing device. Numerous other variations will be apparent tothose of skill in the art having the benefit of the disclosure herein.

The communication interface(s) 114 may include one or more interfacesand hardware components for enabling communication with various otherdevices, such as over the one or more networks 106. Thus, thecommunication interfaces 114 may include, or may couple to, one or moreports that provide connection to the network(s) 106 for communicatingwith the well logging computing device(s) 104, and/or the informationserver computing device(s) 108. For example, the communicationinterface(s) 114 may enable communication through one or more of a LAN(local area network), WAN (wide area network), the Internet, cablenetworks, cellular networks, wireless networks (e.g., Wi-Fi) and wirednetworks (e.g., fiber optic, Ethernet, Fibre Channel,), directconnections, as well as close-range communications, such as BLUETOOTH®,and the like, as additionally enumerated below.

The one or more networks 106 may include any type of network, includinga LAN, such as an intranet; a WAN, such as the Internet; a wirelessnetwork, such as a cellular network; a local wireless network, such asWi-Fi; short-range wireless communications, such as BLUETOOTH®; a wirednetwork including fiber optics, Ethernet, Fibre Channel, or any othersuch network, a direct wired connection, or any combination thereof.Accordingly, the one or more networks 106 may include both wired and/orwireless communication technologies. Components used for suchcommunications can depend at least in part upon the type of network, theenvironment selected, or both. Protocols for communicating over suchnetworks are well known and will not be discussed herein in detail.Accordingly, the visualization computing device(s) 102, the well loggingcomputing device(s) 104, and the information server computing device(s)108 are able to communicate over the one or more networks 106 usingwired or wireless connections, and combinations thereof.

The well logging computing device(s) 104 may include one or moreprocessors 140, one or more communication interfaces 142, and one ormore computer-readable media 144. In some examples, the well loggingcomputing device(s) 104 may have a hardware configuration similar to thevisualization computing device(s) 102 discussed above. For example, theone or more processors 140 may include any of the examples of processors112 discussed above, the one or more communication interfaces 142 mayinclude any of the examples of communication interfaces 114 discussedabove, and the one or more computer-readable media 144 may include anyof the examples of computer-readable media 116 discussed above.

The computer-readable media 144 on the well logging computing device(s)104 may include a well logging program 146 for generating one or more ofthe well logs 120. For example, the well logging program 146 may receiveraw sensor data 148 from a well logging device 150 that may be insertedinto a borehole 154. In the illustrated example, the well logging device150 is attached to a drill string 156, and may perform sensingoperations while the drill string 156 is used for drilling the borehole154. In other examples, the well logging device 150 may be inserted intothe borehole 154 after the borehole 154 has been drilled. The welllogging device 150 may include various types of sensors for detectingwell parameters, e.g., parameters of the earth 158 adjacent to theborehole 154.

In some examples, the well logging device 150 may include a gamma rayemitter 160, such as with a radioactive source (e.g., Cs-137, Co-60, orthe like), that emits gamma rays into the earth 158 for measuringdensity or the like. The well logging device 150 may further include oneor more sensors 162, 164, such as short range sensor 162 and a longerrange sensor 164 that detect gamma rays not absorbed by the earth 158.In some cases, the short range sensor 162 may be used to determine theeffects of the casing or other well materials, if any, on the longerrange sensor 164. The gamma rays may enter the surrounding earth androcks where some of the rays are absorbed and others are reflected backto the sensors 162, 164.

As one non-limiting example, suppose the well logging device 150includes a Cs-137 gamma ray source, which irradiates the formation with662 keV gamma rays. These gamma rays may interact with electrons in theformation through Compton scattering and lose energy. Once the energy ofthe gamma ray has fallen below 100 keV, photoelectric absorptiondominates, i.e., gamma rays are eventually absorbed by the formation.The amount of energy loss by Compton scattering may be related to thenumber electrons per unit volume of formation. In some cases, the gammaray energy loss may be related to the amount of matter per unit volume,i.e., formation density.

The gamma ray sensors 162 and 164 may detect surviving gamma rays andthe detected gamma rays may be sorted into several energy windows. Thequantity of higher-energy gamma rays detected may correspond toformation density. The quantity of lower-energy gamma rays maycorrespond to the average atomic number of the formation, and thus, mayindicate lithology. Because there may be a large contrast between thedensity of the minerals in the formation and the density of porousfluids, porosity may be derived from measured formation bulk density.

Additionally, in other examples, other types of well-logging devices 150may be used. For example, rather than including a gamma ray emitter 160on the well logging device 150, the well logging device 150 may insteadbe configured to detect naturally occurring gamma radiation tocharacterize the rock or sediment adjacent to the borehole 154. Forexample, different types of rock may emit different amounts anddifferent spectra of natural gamma radiation. For instance, shales mayemit more gamma rays than other sedimentary rocks, such as sandstone,gypsum, salt, coal, dolomite, or limestone because radioactive potassiumis a common component in the content of formations including shale. Thedifference in radioactivity between shales and sandstones/carbonaterocks, etc., allows the well logging device 150 to be used todistinguish between shales and non-shales. Thus, the presence or absenceof gamma rays in a borehole may be an indication of the amount of shalein the surrounding formation.

The information server computing device(s) 108 may include one or moreweb servers or other computing devices, such as discussed above, and mayinclude or may access one or more formation databases 170. In someexamples, the information server computing device(s) 108 may be accessedby the visualization computing device 102 to obtain formationinformation 172, which may be downloaded and stored in the formationinformation data structure 124. The data visualization program 118 maythen access this formation information data structure 124 whengenerating the GUI on the display 130. In other examples, the datavisualization program 118 may access the formation informationdatabase(s) 170 on the information server computing device(s) 108 whengenerating the GUI, rather than receiving the formation information 172in advance. In some cases, the information server computing device 108may be publicly available, while in other cases, the information servercomputing device may be private and/or may be accessible based onpayment of a fee or the like.

FIG. 2 illustrates an example GUI 200 that may be generated forvisualizing data according to some implementations. The GUI 200 providesways to visualize sensor data collected from well boreholes, such asgamma ray measurements used to determine density and porosity of thegeological structures adjacent to the borehole. In this example, the GUI200 includes well log metadata 202, two well log visualizations 206 and208, and a formation type visualization 210 of well log data for asingle selected well. The well log metadata 202 includes wellinformation metadata 212 and well log metadata 214. The well informationmetadata 212 may include a file number of the well log(s) for the welland American Petroleum Institute (API) units. The gamma ray API unit isdefined as 1/200 of the difference between the count rate recorded by alogging tool in the middle of the radioactive bed and that recorded inthe middle of the nonradioactive bed.

Additional well information metadata 212 may include the name of thewell operator, the well name, the spud date, a well bore description,latitude and longitude of the well, well status (e.g., active orinactive), and well type. Furthermore, the well log information metadata214 may include the company managing the well, the state and county inwhich the well is located, the name of the field in which the well islocated, the log date, the service company that provided the well log,and the well name. Furthermore, while several types of metadata areillustrated in the example of FIG. 2, additional or alternative types ofmetadata may in be included in other examples, as will be apparent tothose of skill in the art having the benefit of the disclosure herein.

The example GUI 200 of FIG. 2 further includes the two well logvisualizations 206, 208, and a formation type visualization 210 for theidentified well. The well log visualization 206 provides a visualdepiction of gamma ray data from a gamma ray well log generated usingthe techniques discussed above. Further, the well log visualization 208provides a visual depiction of a casing collar locator (CCL) log. Inwell logging, the CCL log may be used for depth control. When combinedwith a gamma ray log, the CCL log allows depth correlation of acased-hole logging run with open-hole logs, which enables subsequentdownhole operations such as perforating. In some cases, the CCL log mayserve as a primary depth control for cased holes and may enable the logoutput to be correlated with previous logs and known casing features.

The well log visualizations 206 and 208 each include a plurality ofcells 216. Each cell 216 may be representative of specified unit ofdepth. Further, each cell 216 may include a plurality of subcells (notshown in FIG. 2 for clarity of illustration) corresponding to a smallerunit of depth. In the well log visualization 206, each cell 216 (orsubcell in other examples) has a graphic effect applied based on a valueof the gamma ray radiation measured at the corresponding depth.Similarly, in the well log visualization 208, each cell 216 (or subcellin other examples) has a graphic effect applied based on a value of theCCL measurement at the corresponding depth. Examples of graphic effectsmay include at least one of a selected color, a selected pattern, aselected brightness, or the like, that corresponds to a value of thegamma ray radiation as set forth in a scale 220. Similarly, the CCLvisualization 208 may have its own scale 221. Thus, for eachvisualization 206, 208, the respective scale 220, 221 may be determinedbased on the range of values of the parameter being presented. Further,the scale 220 for gamma ray visualization 206 may have the same graphiceffects or may have different graphic effects as the scale 221 for theCCL visualization 208.

In addition, the cells 216 are arranged in a series of rows and columnsto create blocks 222 of the cells 216. Each block 222 may correspond toan individual geological formation, and the blocks 222 and cells 216 ineach block 222 may be ordered in a sequence according to the order inwhich the geological formations occur in the ground. The continuity ofthe cell layout may be broken at the start of each subsequent formationtop so that cells belonging to the same formation are grouped into thesame single block 222 of cells. A gap or break 224 is inserted betweentwo adjacent blocks 222 as an indicator to visually indicate the end ofone formation and the beginning of the next formation or otherwise toindicate a change in formation. Thus, each block 222 of cells 216 mayrepresent a different formation. Further, while a break 224 is used asan indicator of a change in formation in this example, in otherexamples, other types of indicators may be used, such as a bolded line,different colored line, and so forth.

In addition, the overall width of the well log visualizations 206, 208may be set to a default width (e.g., 100 feet in this example, asindicated by width scale 226) and may be configurable by a userdepending on the depth interval desired to be represented in a singlerow. For example, in the default case, each row corresponds to 100 feetof depth, each cell may correspond to 5 feet of depth, and each subcellmay correspond to ½ foot of depth. Accordingly, in the illustratedexample, each row includes 20 cells, with each cell including 10subcells in a two-layer configuration (not shown in FIG. 2 for clarityof illustration). Further, a vertical depth scale 228 may be included onthe side of each well log visualization 206, 208 to indicate the depthat which each new formation begins, corresponding to the start of a nextblock 222 following a break 224. Thus, the GUI 200 herein provides acompact intuitive view of well log data that conveys meaningfulinformation representative of one or more measured parameters. Inaddition, the GUI 200 provides a clear indication of the number andlocation of the different geological formations relative to each other.

The formation visualization 210 includes formation labels 230 thatidentify the name and description of each formation at the beginning ofthe respective formation. Further, the formation visualization includesblocks 232 having a height that matches the height of the respectiveblocks 222 in the well log visualizations 206 and 208. The blocks 232may be separated by gaps 234 that match the breaks 224 between theblocks 222 in the well log visualizations 206 and 208. Further, each ofthe blocks 232 may include a graphic effect, such as at least one of acolor, pattern, level of brightness, or the like. As one example, thegraphic effect in each block 232 may corresponding to a predominantgraphic effect of the corresponding well log block 222 (e.g., based ontaking an average of the parameter over the entire block 222).Alternatively, the blocks 232 may have a graphic effect that isunrelated to the well log parameters, and is instead related to adifferent parameter, such as formation type. For example, differentformation types may be assigned different graphic effects.

Furthermore, while the example GUI 200 of FIG. 2 includes multiplevisualizations of multiple well logs corresponding to a single well, inother examples, the GUI 200 may be configured to present visualizationsof logs from two or more different wells to enable side-by-sidecomparison of the parameters of the different wells, as discussedadditionally below. Accordingly, implementations herein are not limitedto the specific examples illustrated and described herein.

FIG. 3 illustrates an enlarged view 300 of a log data visualizationincluding details of individual subcells within individual cellsaccording to some implementations. As mentioned above, each cell 216 mayinclude a plurality of subcells 302. In this example, each cell 216includes 10 subcells 302, with an upper row of five subcells 302 and alower row of five subcells 302 in each cell 216. Additionally, in otherexamples, the number of subcells may be 2, 4, 6, 8, 12, or so forth.Alternatively, in other examples, there may be a single row of subcells302 per cell 216, and thus an odd or even number of subcells 302 percell.

In some cases, the number of subcells 302 per cell 216 may correspond tounits of measurement (e.g., depth) used for determining sensor datawindows. For instance, if each cell corresponds to five feet of adepth-series signal (i.e., a parameter as measured while the welllogging device moves 5 feet within the well borehole), then each subcellmay correspond to 0.5 feet, e.g., the average of the parameter asmeasured over the corresponding 0.5 feet of depth in some examples. Asanother example, if each cell 216 corresponds to 2.5 meters of depth,then each subcell 302 may correspond to 25 cm of depth. Thus, each cell216 may correspond to a first unit of depth and each subcell 302 maycorrespond to a subunit that is an equal subdivision of the unit ofdepth.

In this example, the enlarged view 300 corresponds to a rectangle 304shown on the GUI 200 overlapping the visualization 206 discussed abovewith respect to FIG. 2. The rectangle 304 overlaps a first block 222(1)and a second block 222(2) of the visualization 206. The enlarged view300 further shows that there is a break 224 between the last row of thefirst block 222(1) and the first row of the second block 222(2), whichserves as an indicator to indicate that the first row of the secondblock 222(2) is the beginning of a new (different) geological formation.As mentioned above, and as discussed additionally below, the graphiceffect selected for each subcell 302 may correspond to a parameter valuemeasured at the depth corresponding to the respective subcell 302, whichmay also be indicated by the scale 220 or other scale corresponding tothe respective log visualization.

FIG. 4 illustrates an example LAS data structure 400 of an LAS file fora well log according to some implementations. For instance, the raw datafor a well may be converted to one or more LAS files. A single LAS filemay contain one type of data obtained from a well borehole, or maycontain any number data sets (also referred to as “curves”) from theborehole. Common curves found in a LAS file may include natural gamma,travel time, or resistivity logs. Accordingly, the LAS file datastructure may include metadata 402 and log data including loggedvariables 404 and logs 406.

The metadata 402 may include version information 408, which may includean indication of a version 410 of the Canadian Well Logging Society(CWLS) LAS file being used. The metadata 402 may further include wellinformation 412, such as a start depth, a stop depth, a measurement stepsize, a null value indicator, a company name, a well name, a field name,a location name, a county name, a service company name, a date, a uniquewell identifier, and a state in which the well is located, as indicatedat 414. The null value may be inserted into the log data to take theplace of missing data.

In addition, the logged variables 404 may include curve information 416that lists the included curves, such as a depth, line speed, linetension, actual depth, gamma ray, and CCL. In addition, the logs 406 mayinclude parameter (attribute) information 420, i.e., the measured dataor received sensor data, which in this example includes measurements fordepth as indicated at 422, line speed as indicated at 424, line tensionas indicated at 426, actual depth as indicated at 428, gamma ray data asindicated at 430, and CCL data as indicated at 432. Furthermore, whilecertain measured parameters are shown and described in this example, inother examples, other parameters may be included in the LAS file datastructure 400, as enumerated elsewhere herein.

FIG. 5 illustrates an example of the formation information datastructure 124 according to some implementations. In this example, theformation information data structure 124 includes a formation key 502, aformation description 504, and a formation depth 506. For example, theformation information data structure 124 may be determined for aparticular location of a particular well, and may be based oninformation obtained from a formation database such as may be availablefrom the United States Geological Survey or other public or privatedatabases. The formation key 502 for each respective formation may beincluded in the GUIs described herein, such as at the correspondingdepth to indicate the start of a new formation (formation top).

FIG. 6 includes a flow diagram illustrating an example process accordingto some implementations. The process is illustrated as a collection ofblocks in a logical flow diagram, which represents a sequence ofoperations, some or all of which may be implemented in hardware,software or a combination thereof. In the context of software, theblocks may represent computer-executable instructions stored on one ormore computer-readable media that, when executed by one or moreprocessors, program the processors to perform the recited operations.Generally, computer-executable instructions include routines, programs,objects, components, data structures, and the like, that performparticular functions or implement particular data types. The order inwhich the blocks are described should not be construed as a limitation.Any number of the described blocks can be combined in any order and/orin parallel to implement the process, or alternative processes, and notall of the blocks need be executed. For discussion purposes, the processis described with reference to the environments, frameworks, and systemsdescribed in the examples herein, although the process may beimplemented in a wide variety of other environments, frameworks, andsystems.

FIG. 6 is a flow diagram illustrating an example process 600 forgenerating a GUI according to some implementations. In some examples,the process 600 may be executed by the visualization computing device(s)102 or other suitable computing device(s) by executing the datavisualization program, such as for generating a GUI 601 or other welllog visualization GUIs. The flow diagram includes a plurality ofoperations for generating and presenting the GUI 601 with visualizations603 and 605 of well log data and a visualization 607 of formationsaccording to some implementations herein. In some examples, the GUI 601may correspond to the GUI 200 discussed above with respect to FIG. 2. Inother examples, the GUI 601 may correspond to other GUIs that may begenerated using the techniques described herein.

At 602, the computing device may receive an input to cause the computingdevice to generate the GUI 601. For example, the user of thevisualization computing device may make a user input to cause the GUI601 to be presented. In other examples, the input may come from anotherapplication or computer program, or through other type of triggeringevent.

At 604, the computing device may access or otherwise receive log datafor one or more specified wells or log data specified by or otherwiseassociated with the input.

At 606, the computing device may determine one or more depth-series datafrom the log data. For example, the computing device may receive a LASfile, as discussed above with respect to FIG. 4, and may read the depthseries data from various logs included in the LAS file. The depth serieslog data from the LAS file may be used for generating one or more logdata visualizations 603 and/or 605.

At 608, the computing device may receive formation depth information andformation keys. For example, the computing device may access theformation information data structure 124 discussed above with respect toFIG. 5, such as for determining formation types, formation depths,formation keys and so forth.

At 610, the computing device may determine formations and formation keysfor the well, e.g., based on the well location.

At 612, the computing device may determine formation top depths andorder of formation blocks when a formation block visualization 607 is tobe presented in the GUI.

At 614, the computing device may determine spatial scale layout andbreak locations between blocks. For example, based on the formation topinformation and depth information from 612, the computing device maydetermine the locations of breaks 224 between respective blocks 222 ofcells. Further, the computing device may determine a layout of the logdata visualization based on the total depth, the number of formations,and a desired level of granularity. As mentioned above, a defaultsetting may be 20 cells per row and ten subcells per cell, but thedefault may be adjusted by the user or by the data visualizationprogram, such as in the case of an extremely deep or shallow well, alarge number of different formations, or the like. In addition, in somecases, the computing device may determine the parameter value for eachsubcell that will be presented in the GUI 601. In other cases, if thesubcell values have already been determined, the subcell values may beretrieved from a subcell value data structure, as discussed additionallybelow, rather than having to recompute the subcell values each time theGUI is rendered.

At 616 the computing device may determine amplitude scales (e.g., colorgradients, cross-hatching or shading gradients, brightness gradients,and so forth) for graphic effects to apply to individual subcells. Asone example, the computing device may determine the amplitude scale foreach visualization based on a low end and high end of the respectivemeasured parameter in the log data. In some examples, amplitude scales,such as color scales, may be computed for each log to ensure thatoutliers do not skew the scale gradient, which might make the rest ofthe values indistinguishable. This can be achieved in various differentways. For instance, colors or other graphic effects can be mapped topercentile values of the log (e.g., one color or graphic pattern for 10to 15 percentile). Outliers may then fall into a single color or pattern(e.g., 99 to 100 percentile for high outliers), and may be highlightedwith a unique border around the subcell, or other graphicallydistinguishing feature. Additionally, in some examples, colors orpatterns may be mapped using Jenks natural breaks optimization (see,e.g., Jenks, George F. 1967. “The Data Model Concept in StatisticalMapping”, International Yearbook of Cartography 7: 186-190.), aclustering technique used to define optimal color scale for parametermapping, or various other clustering techniques.

At 618, the computing device may render and present the GUI according tothe determined layout and amplitude scales determined above. Thecontinuity of the cell layout is broken at each formation top by thebreaks 224 such that cells belonging to a respective formation arearranged in a single group as a block 222 of cells. The overall width ofthe visualizations 603 and 605 can also be configured by the userdepending on the depth interval represented in a single line. As onenon-limiting example, for a line accounting for 100 feet of depth, thevisualization may include 100/5=20 cells per line, and, with each cellcorresponding to 5 feet of depth and each subcell corresponding to ahalf foot of depth. Thus, the average value of the depth signal in each0.5 foot window (or other selectable unit of depth) can be representedin each sub-cell colored, patterned, etc., according to the definedamplitude graphic effect scale. In addition, in the case of missing logdata values (e.g., corresponding to “−999.25” in the logs in FIG. 4) thecorresponding subcells may be distinguished, such as by being presentedin gray, being blacked out, or the like. The technique discussed abovemay be employed for a particular well or well log, or may be employedfor presenting logs from multiple different cells side by side to enablecomparison of results from two or more wells.

FIG. 7 illustrates an example 700 of determining subcell values forsubcells of a cell according to some implementations. In this example, asignal 702 received from a sensor has an amplitude that varies in thehorizontal direction, as illustrated, from a lower value on the left toa larger value on the right. The signal 702 may correspond to a measuredparameter of log data such as measured gamma ray values, CCL locationvalues, line tension values, resistivity, and so forth. Furthermore, thesignal 702 is correlated to a distance or depth of sensor travel, whichmay be divided into a plurality of units, as indicated by arrow 704,each of which may correspond to a cell 216 to be generated in acorresponding GUI. For example, as discussed above with respect to FIG.1, as a sensor is moved inside a well borehole, the measured amplitudeof the sensor signal may vary with the change in depth.

As enumerated elsewhere herein, the depth unit 704 may be selected bythe user or by default, and may be a number feet, a number meters, orthe like. In this example, suppose that the depth unit is five feet,although implementations herein are not limited to any particular depthunit. In addition, the depth unit 704 may be divided into a plurality ofsubunits 706, each corresponding to a subcell of the cell 216. In thisexample, the depth unit 704 is divided into 10 subunits 706, althoughmore or fewer subunits may be used in other examples. Accordingly, ifthe depth unit 704 is five feet, then each subunit 706 may correspond to0.5 feet, and the cell 216 may be divided into 10 subcells 708, 710,712, 714, 716, 718, 720, 722, 724, and 726.

Furthermore, in this example, the cell 216 includes a stackedarrangement of the subcells 708-726 in which the subcells 708-726alternate between an upper row 728 and a lower row 730. In FIG. 7, the10 subunits 706 are each assigned a number 1 through 10, and thesenumbers 1-10 are reflected in the subcells 708-726 of the cell 216 toshow the corresponding subcell to which the corresponding sensor signalparameter value is assigned. Thus, the sensor signal parameter values gofrom the upper row 728 to the subcell immediately below in the lower row730, and then back to the next subcell in the upper row in a zigzagpattern, as illustrated. This arrangement provides a compactvisualization of the sensed parameter information corresponding to thesubunits 706. Alternatively, in other examples, other arrangements ofthe subcells, such as a single row of subcells, may be used.Additionally, other patterns may be used for assigning the sensor signalvalues to the respective subcells. For example, the upper row 728 ofsubcells may be populated entirely before populating the lower row 730of subcells, and so forth.

To generate a visualization of the sensor signal 702, the visualizationcomputing device may determine an average value 732 of the signalmeasured over each 0.5 foot window, such as an average of the sensorsignal amplitude measured over each subunit 706. The average values 732of the subunits 706 may be correlated to a graphic effect to bedisplayed within the depicted cell layout of each respective subcell ofeach cell 216. In addition, the average values 732 of the subunits 706may be stored in the subcell parameter value data structure 122.Accordingly, the subcell parameter value data structure 122 may be usedsubsequently each time a visualization of the respective sensor data isdesired, without having to recompute the average sensor values for therespective sensor data.

To determine the graphic effect to apply to individual subcells, thecomputing device may determine an upper limit and a lower limit of thesensor signal amplitude, and may apply these limits to a scale 734 ofgraphic effects for the parameter values. As mentioned above, in someexamples, amplitude color scales or other graphic effects scales may bedetermined for each data log to ensure that outliers do not skew thescale gradient, which might otherwise make the rest of the averagesensor values indistinguishable. This can be achieved in variousdifferent ways. As one example, colors or other graphic effects can bemapped to percentile values of the sensor data (e.g., one color orgraphic pattern for 10 to 15 percentile). Outliers may then fall into asingle color or pattern (e.g., 99 to 100th percentile for highoutliers), and, in some cases, may be highlighted with unique borderaround the subcell, or other graphically distinguishing feature.Additionally, in some examples, colors or patterns may be mapped usingJenks natural breaks optimization or various other clusteringtechniques.

In this example, suppose that the sensor signal amplitude may varybetween a range of 0 and 165, and that the scale 734 is divided intoeight different graphic effects, such as eight different graphicpatterns. As indicated at 736, the computing device may determine thegraphic effect to apply to each subcell 708-726 based on the averagevalue per specified subunit of depth 732 in the subcell parameter valuedata structure 122. As an example, suppose that the average amplitudevalue 732 of the signal 702 for the first subunit is 60.05. Accordingly,as indicated at 740, the computing device may apply to the first subcell708 the graphic effect from the scale 734 assigned to values between41.25 and 61.875. Similarly, suppose that the average amplitude value732 of the signal 702 for the second subunit is 62.55. Thus, asindicated at 742, the computing device may apply to the second subcell710 the graphic effect from the scale 734 assigned to values between61.875 and 82.5. Accordingly, when presenting the visualization of thelog data corresponding to the sensor signal 702, the computing devicemay populate all of the subcells and cells as discussed above.

Additionally, while the scale 734 is illustrated in this example asbeing divided into eight distinct graphic effects, more or fewerdivisions may be used in other examples. For instance, in some cases,the scale 734 may be a gradient with no clear demarcations betweengraphic effects, such as a gradient of one or more colors, a grayscalegradient from dark to light, or vice versa, a brightness gradient, andso forth. Numerous other variations will be apparent to those of skillin the art having the benefit of the disclosure herein.

FIG. 8 illustrates an enlarged view 800 of applying additional graphiceffects to the subcells to convey additional information according tosome implementations. As mentioned above, each cell 216 may include aplurality of subcells 302. In this example, each cell 216 includes 10subcells 302, with an upper row of five subcells 302 and a lower row offive subcells 302 in each cell 216. Additionally, in other examples, thenumber of subcells may be 2, 4, 6, 8, 12, or so forth. Alternatively,other examples, there may be a single row of subcells 302 per cell 216,and thus an odd or even number of subcells 302 per cell.

In this example, the enlarged view 800 corresponds to a rectangle 804shown on the GUI 200 overlapping the visualization 206 discussed abovewith respect to FIG. 2. The rectangle 804 overlaps a first block 222(1)and a second block 222(2) of the visualization 206. The enlarged view800 further shows that there is a break 224 between the last row of thefirst block 222(1) and the first row of the second block 222(2), whichserves as an indicator to indicate that the first row of the secondblock 222(2) is the beginning of a new (different) geological formation.As mentioned above, the graphic effect selected for each subcell 302 maycorrespond to a parameter value (e.g., an average amplitude of a sensorsignal in some cases) measured at a window of depth corresponding to therespective subcell 302, which may also be indicated by the scale 220 orother scale corresponding to the respective log visualization.

In this example, the additional graphic effects may be used to indicatea trend of parameter values of the log data, such as for indicating anupward trend, a downward trend, a stable trend, etc., of the parametervalue. As one example, for the sensor signal value at a first depth,there may be no graphic effect applied. For every other depth andcorresponding subcell, the computing device may determine the parametervalue of the sensor signal for the subcell and may determine adifference between the parameter value of the sensor signal at theimmediately previous subcell (depth) and the parameter value of thecurrent cell to obtain a resulting value. If the resulting value ispositive (up), a first additional graphic effect may be applied to thesubcell in addition to the graphic effect indicative of the parametervalue. For instance, as illustrated at 806, the first additional graphiceffect may be an emboss effect that shows the subcell in a raised state.

Similarly, if the resulting value is negative (down), a secondadditional graphic effect may be applied to the subcell in addition tothe graphic effect indicative of the parameter value. For instance, asillustrated at 808, the second additional graphic effect may be a debosseffect that shows that subcell in a depressed or lowered state.Furthermore, if the resulting value is zero, a third graphic effect orno graphic effect might be applied to the respective subcell, asillustrated at 810. Additionally, in some cases, rather than merely notbeing equal to zero, a minimum threshold may be required to be exceededto show an upward trend or lowering trend. For example, the resultingvalue may be required to more or less than 5 percent of the previousparameter value to show an upward or downward trend, respectively, andotherwise the trend may be displayed as stable. Numerous othervariations will be apparent to those of skill in the art having thebenefit of the disclosure herein.

FIG. 9 illustrates an example GUI 900 for comparing a parameter from twodifferent wells concurrently according to some implementations. In thisexample, the user may select a first well and a second well, and mayselect a parameter to be displayed for the respective selected wells.For instance, as one of the wells, suppose that the user selects thewell discussed above with respect to FIG. 2, and the gamma ray logparameter, which causes the computing device to present the gamma rayvisualization 206 and the associated formation visualization 210discussed above with respect to FIG. 2. In addition, suppose that theuser also selects a second well, which causes the computing device topresent a second gamma ray visualization 902 and a second formationvisualization 904.

In this example, the second well has a depth that is substantiallydeeper than that of the first well. Accordingly, the scale of thevisualizations 902 and 904 for the second well may be different fromthat of the visualizations 206 and 210 for the first well. In thisexample, as indicated at 906, each row of the visualization 902 maycorrespond to 140 feet, rather than 100 feet as in the visualization206. Thus, as illustrated, each of 20 cells 216 in each row of thevisualization 902 may correspond to seven feet of depth, rather thanfive feet. Alternatively, the cells 216 may correspond to five feet ofdepth and each row of the visualization 902 may include 28 cells ratherthan 20 (not shown in this example). Other variations will also beapparent to those of skill in the art having the benefit of thedisclosure herein.

Furthermore, the visualization 904 may include a graphic effect scale908 that includes the same graphic effects as the scale 220 associatedwith the visualization 206. This enables a like-to-like comparison ofthe two visualizations 206 and 904, even though the scales 908 and 220may have entirely different upper and lower parameter values. Thus,implementations herein may enable side-by-side comparison of gamma raydata collected using different techniques and/or different sensor types.

In addition, the formation visualization 904 may be presented in amanner similar to that discussed above for the formation visualization210. For example, formations having the same formation name and/or keymay be presented using the same graphic effects, such as the same color,same pattern, etc. Furthermore, while two visualizations are presentedfor side-by-side comparison in this example, in other examples, three ormore visualizations may be presented side-by-side, depending in part ondisplay screen size and/or resolution.

The example processes described herein are only examples of processesprovided for discussion purposes. Numerous other variations will beapparent to those of skill in the art in light of the disclosure herein.Further, while the disclosure herein sets forth several examples ofsuitable frameworks, architectures and environments for executing theprocesses, the implementations herein are not limited to the particularexamples shown and discussed. Furthermore, this disclosure providesvarious example implementations, as described and as illustrated in thedrawings. However, this disclosure is not limited to the implementationsdescribed and illustrated herein, but can extend to otherimplementations, as would be known or as would become known to thoseskilled in the art.

Various instructions, processes, and techniques described herein may beconsidered in the general context of computer-executable instructions,such as programs stored on computer-readable media, and executed by theprocessor(s) herein. Generally, programs include computer-readableinstructions, routines, modules, applications, objects, components, datastructures, executable code, etc., for performing particular tasks orimplementing particular abstract data types. These programs and the likemay be executed as native code or may be downloaded and executed, suchas in a virtual machine or other just-in-time compilation executionenvironment. Typically, the functionality of the programs may becombined or distributed as desired in various implementations. Animplementation of these programs and techniques may be stored oncomputer storage media or transmitted across some form of communicationmedia.

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described. Rather,the specific features and acts are disclosed as example forms ofimplementing the claims.

What is claimed:
 1. A system comprising: a display; one or moreprocessors in communication with the display; and one or morenon-transitory computer-readable media maintaining executableinstructions, which, when executed by the one or more processors,program the one or more processors to perform operations comprising:receiving log data including depth-series data for a parametercorresponding to a well; receiving formation information for the well;determining an average parameter value of the depth series data forindividual subunits of depth over a larger unit of depth; determining ascale of graphic effects corresponding to parameter values between a lowparameter value and a high parameter value; and presenting, on thedisplay, a visualization of the depth-series data, the visualizationincluding a plurality of cells arranged in a plurality of rows, eachcell corresponding to the larger unit of depth and including a pluralityof subcells corresponding to the subunits of depth, each subcellpresented with a respective graphic effect corresponding to a parametervalue determined at a corresponding depth, the graphic effectcorresponding to the parameter value on the scale of graphic effects,the visualization further including, based on the formation information,an indicator between a first plurality of the rows and a secondplurality of the rows to indicate a change in geological formation. 2.The system as recited in claim 1, the operations further comprising:determining, based on the formation information, a plurality offormations corresponding to the well; and grouping the cells accordingto the plurality of formations based on a depth associated with eachcell and each formation.
 3. The system as recited in claim 2, theoperations further comprising including the indicator between each groupof cells, wherein the indicator includes at least one of a break betweeneach group of cells or a line between each group of cells.
 4. The systemas recited in claim 1, the operations further comprising: receiving asensor signal as the depth series of data, the sensor signalcorresponding to the parameter and including an amplitude; anddetermining the average parameter value of the depth series data forindividual subunits of depth over a larger unit of depth by determiningan average of the amplitude over each individual unit of depth.
 5. Thesystem as recited in claim 2, the operations further comprisingpresenting, on the display, a formation visualization concurrently withthe visualization of the depth series data, the formation visualizationincluding a plurality of blocks corresponding to respective geologicalformations, wherein the plurality of blocks are arranged in order of therespective geological formations according to depth, wherein formationtop indicators are included between the blocks to indicate a change information.
 6. The system as recited in claim 1, the operations furthercomprising: for a first subcell, determining a difference between theaverage parameter value for the first subcell and the average parametervalue for an immediately previous subcell; and including an additionalgraphic effect based on the difference when presenting the first subcellon the display.
 7. The system as recited in claim 1, wherein the well isa first well, the operations further comprising: receiving log data forthe parameter for a second well; and presenting a second visualizationon the display concurrently with the first visualization, the secondvisualization including a plurality of rows of cells having subcellsincluding graphic effects determined based on the log data for thesecond well.
 8. A method comprising: receiving, by one or moreprocessors, log data including depth-series data for a parametercorresponding to a well; determining a parameter value of the depthseries data for individual subunits of depth over a larger unit ofdepth; determining a scale of graphic effects corresponding to parametervalues for the depth-series data; and presenting, on a display, avisualization of the depth-series data, the visualization including aplurality of cells arranged in a plurality of rows, each cellcorresponding to the larger unit of depth and including a plurality ofsubcells corresponding to the subunits of depth, each subcell presentedwith a respective graphic effect corresponding to the parameter valuedetermined at a corresponding depth, the graphic effect corresponding tothe parameter value on the scale of graphic effects.
 9. The method asrecited in claim 8, further comprising: receiving formation informationfor the well; and presenting the visualization to include, based on theformation information, an indicator between a first plurality of therows and a second plurality of the rows to indicate a change ingeological formation.
 10. The method as recited in claim 9, furthercomprising: determining, based on the formation information, a pluralityof formations corresponding to the well; grouping the cells according tothe plurality of formations based on a depth associated with each celland each formation; and including the indicator between each group ofcells, wherein the indicator includes at least one of a break betweeneach group of cells or a line between each group of cells.
 11. Themethod as recited in claim 9, further comprising presenting, on thedisplay, a formation visualization concurrently with the visualizationof the depth-series data, the formation visualization including aplurality of blocks corresponding to respective geological formations,wherein the plurality of blocks are arranged in order of the respectivegeological formations according to depth, wherein formation topindicators are included between the blocks to indicate a change information.
 12. The method as recited in claim 8, further comprising:receiving a sensor signal as the depth series of data, the sensor signalcorresponding to the parameter and including an amplitude; anddetermining the parameter value of the depth-series data for individualsubunits of depth by determining an average of the amplitude over eachindividual unit of depth.
 13. The method as recited in claim 8, furthercomprising: for a first subcell, determining a difference between theparameter value for the first subcell and the parameter value for animmediately previous subcell; and including an additional graphic effectbased on the difference when presenting the first subcell on thedisplay.
 14. The method as recited in claim 8, wherein the well is afirst well, the method further comprising: receiving log data for theparameter for a second well; and presenting a second visualization onthe display concurrently with the first visualization, the secondvisualization including a plurality of rows of cells having subcellsincluding graphic effects determined based on the log data for thesecond well.
 15. One or more non-transitory computer-readable mediastoring instructions which, when executed by one or more processors,program the one or more processors to: receive log data including adepth-series of data for a parameter; determine a parameter value of thedepth series data for individual subunits of depth corresponding to alarger unit of depth; determine a scale of graphic effects correspondingto parameter values for the depth-series data; and present, on adisplay, a visualization of the depth-series data, the visualizationincluding a plurality of cells arranged in a plurality of rows, eachcell corresponding to the larger unit of depth and including a pluralityof subcells corresponding to the subunits of depth, each subcellpresented with a respective graphic effect corresponding to theparameter value determined at a corresponding depth, the graphic effectcorresponding to the parameter value on the scale of graphic effects.16. The one or more non-transitory computer-readable media as recited inclaim 15, wherein: the depth-series data is for a well, and the one ormore processors are further programmed to: receive formation informationfor the well; and present the visualization to include, based on theformation information, an indicator between a first plurality of therows and a second plurality of the rows to indicate a change ingeological formation.
 17. The one or more non-transitorycomputer-readable media as recited in claim 16, wherein the one or moreprocessors are further programmed to: determine, based on the formationinformation, a plurality of formations corresponding to the well; groupthe cells according to the plurality of formations based on a depthassociated with each cell and each formation; and include the indicatorbetween each group of cells, wherein the indicator includes at least oneof a break between each group of cells or a line between each group ofcells.
 18. The one or more non-transitory computer-readable media asrecited in claim 16, wherein the one or more processors are furtherprogrammed to present, on the display, a formation visualizationconcurrently with the visualization of the depth-series data, theformation visualization including a plurality of blocks corresponding torespective geological formations, wherein the plurality of blocks arearranged in order of the respective geological formations according todepth, wherein formation top indicators are included between the blocksto indicate a change in formation.
 19. The one or more non-transitorycomputer-readable media as recited in claim 15, wherein the one or moreprocessors are further programmed to: receive a sensor signal as thedepth series of data, the sensor signal corresponding to the parameterand including an amplitude; and determine the parameter value of thedepth-series data for individual subunits of depth by determining anaverage of the amplitude over each individual unit of depth.
 20. The oneor more non-transitory computer-readable media as recited in claim 15,wherein the one or more processors are further programmed to: for afirst subcell, determine a difference between the parameter value forthe first subcell and the parameter value for an immediately previoussubcell; and include an additional graphic effect based on thedifference when presenting the first subcell on the display.